Proceedings Paper

Content-based retrieval techniques can be characterized in several ways: by the manner in which image data are indexed, by the level of specificity/generality of the query and response of the system, by the type of query (e.g., iconic or symbolic), and by the kind of information used (intrinsic image features or attached information such as text). The method described in this paper automatically indexes images in the database, and is intended to retrieve specific objects by image query based on inherent image content. Our method is actually quite similar to object recognition except that instead of searching a single image for a given object, an entire database of images is examined. The approach uses linear phase coefficient composite (LPCC) filters to encode and match queries consisting of multiple images (e.g., representative views of an object of interest) against multiple images in the database simultaneously. Retrieval is a two-step process that first isolates those portions of the database containing images that match the query, and then identifies the specific images. Our use of LPCC filters exploits phase information to retrieve specific images that match the query from the database. The results from the experiments suggest that phase information can be used to index and retrieve multiple images from a database in parallel, and that large numbers of operations can be performed simultaneously using a complex number representation. In one experiment well over 100 real correlations were effectively performed by a single complex correlation. Problems encountered in processing video data are discussed.